The advent of efficient methods for isotopic enrichment of proteins with 13C and 15N, together with the development of three- and four-dimensional (3D and 4D) NMR methods, now makes it possible to study in detail the structure and dynamics of proteins in the 15-30 kD molecular weight range, as was demonstrated most recently for the proteins interleukin- 1beta, calmodulin complexed with a fragment of myosin light chain kinase and interferon-gamma. However, the present procedures for data collection and analysis are extremely time consuming, and the spectral resolution obtainable frequently presents a limiting factor. The goal of this proposal is the development of improved and new procedures for the analysis of multi-dimensional NMR spectra. Significant improvements over present methodology are expected to be possible considering that most of the methodology presently does not utilize the advances which have been made in the last decade in the area of signal processing. Improved and new procedures will focus on but not limit to the following: (1) Improvement of the linear prediction methods: improving the stability and computation efficiency of the 1-D and 2-D linear prediction algorithms. (2) Optimization of a priori information: Use of a priori information in NMR data to improve the spectral resolution. (3) Non-linear spectral enhancement: Development of the 3-D maximum entropy method and improving the convergence rate of methods based on iterative deconvolution. (4) Development of fast algorithms: Development of fast routines that make possible the use of algorithms in multi-dimensional space. (5) signal subspace approach: Separation of the signal and the noise subspace to obtain high NMR spectral resolution. (6) Higher-order spectra estimation: Use of high- order statistics to gain a better estimate of dense NMR spectra. (7) Multi-resolution techniques: New signal representation for NMR data to achieve optimal interpretation and processing. (8) Data compression: Compression of multi-dimensional NMR data by removing redundant information for processing, networking, and archiving. (9) Parallel implementation: Development of parallel routines for high-performance parallel computing. Emphasis will be on the development of code which is easily transportable and which will be made freely available to the NMR community. The complexities of the task of developing algorithms and software for advanced processing of multi-dimensional NMR data are substantial and require effective integration of expertise in the areas of NMR and signal processing. This proposal is designed to foster such integration.